
# 配置所依赖的表所处的[任务名字]及[任务所在包的位置]

# -*- coding: utf-8 -*-
from datetime import timedelta
from utils.operators.cluster_for_spark_sql_operator import SparkSqlOperator
from jms.ods.oms.yl_new_customer_activity_sp import jms_ods__yl_new_customer_activity_sp
jms_dwd__dwd_yl_new_customer_activity_sp_base = SparkSqlOperator(
    task_id='jms_dwd__dwd_yl_new_customer_activity_sp_base',
    task_concurrency=1,
    pool_slots=2,
    master='yarn',
    execution_timeout=timedelta(minutes=30),
    email=['rabie.zhuang@jtexpress.com','yl_bigdata@yl-scm.com'],
    name='jms_dwd__jms_dwd__dwd_yl_new_customer_activity_sp_base_{{ execution_date | date_add(1) | cst_ds }}',
    sql='jms/dwd/dwd_yl_new_customer_activity_sp_base/execute.sql',
    driver_cores=1,
    driver_memory='1G',
    executor_cores=2,
    executor_memory='6G',
    num_executors=4,
    conf={
        'spark.dynamicAllocation.enabled': 'true',  # 动态资源开启
        'spark.shuffle.service.enabled': 'true',  # 动态资源 Shuffle 服务开启
        'spark.dynamicAllocation.maxExecutors': 5,  # 动态资源最大扩容 Executor 数
        'spark.dynamicAllocation.cachedExecutorIdleTimeout': 30,  # 动态资源自动释放闲置 Executor 的超时时间(s)
        'spark.executor.memoryOverhead': '2G',  # 堆外内存
        'spark.hadoop.hive.exec.dynamic.partition.mode': 'nonstrict', # 动态分区
        'spark.hadoop.hive.exec.dynamic.partition': 'true',
        'spark.sql.shuffle.partitions': 1,
        'spark.sql.files.maxPartitionBytes': 268435456,
    },
    hiveconf={'hive.exec.dynamic.partition': 'true',
              'hive.exec.dynamic.partition.mode': 'nonstrict',
              'hive.exec.max.dynamic.partitions.pernode': 200,
              'hive.exec.max.dynamic.partitions': 200
              },
    yarn_queue='pro',
)
# 设置依赖
jms_dwd__dwd_yl_new_customer_activity_sp_base << [
    jms_ods__yl_new_customer_activity_sp
]

